Understanding the Natural History of Chronic Hepatitis D: Proposal of a Model for Cost-Effectiveness Studies

Ankita Kaushik, Geoffrey Dusheiko, Chong Kim (), Nathaniel J. Smith, Csilla Kinyik-Merena, Gian Luca Tanna and Robert J. Wong
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Ankita Kaushik: Gilead Sciences, Inc.
Geoffrey Dusheiko: University College London
Chong Kim: Gilead Sciences, Inc.
Nathaniel J. Smith: Maple Health Group
Csilla Kinyik-Merena: Maple Health Group
Gian Luca Tanna: University of Applied Sciences and Arts of Southern Switzerland
Robert J. Wong: Stanford University School of Medicine

PharmacoEconomics - Open, 2024, vol. 8, issue 2, No 13, 333-343

Abstract: Abstract Background As new therapeutic options become available, better understanding the potential impact of emerging therapies on clinical outcomes of hepatits D virus (HDV) is critical. Objective The aim of this study was to develop a natural history model for patients with hepatitis D virus. Methods We developed a model (decision tree followed by a Markov cohort model) in adults with chronic HDV infection to assess the natural history and impact of novel treatments on disease progression versus best supportive care (BSC). The model time horizon was over a lifetime (up to 100 years of age); state transitions and health states were defined by responder status. Patients in fibrosis stages 0 through 4 received treatment; decompensated patients were not treated. Response was defined as the combined response endpoint of achievement of HDV-RNA undetectability/≥2-log10 decline and alanine aminotransferase normalization; response rates of 50% and 75% were explored. Health events associated with advanced liver disease were modeled as the number of events per 10,000 patients. Scenario analyses of early treatment, alternate treatment response, and no fibrosis regression for treatment responders were also explored. Results The model was able to reflect disease progression similarly to published natural history studies for patients with HBV/HDV infection. In a hypothetical cohort of patients reflecting a population enrolled in a recent clinical trial, fewer advanced liver disease events were observed with a novel HDV treatment versus BSC. Fewer liver-related deaths were observed under 50% and 75% response (900 and 1,358 fewer deaths, respectively, per 10,000 patients). Scenario analyses showed consistently fewer advanced liver disease events with HDV treatment compared with BSC, with greater reductions observed with earlier treatment. Conclusion This HDV disease progression model replicated findings from natural history studies. Furthermore, it found that a hypothetical HDV treatment results in better clinical outcomes for patients versus BSC, with greater benefit observed when starting treatment early. This validated natural history model for HBV/HDV infection can serve as a foundation for future clinical and economic analyses of novel HDV treatments that can support healthcare stakeholders in the management of patients with chronic HDV.

Date: 2024
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DOI: 10.1007/s41669-023-00466-3

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